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Article

Assimilation of FY-3D and FY-3E Hyperspectral Infrared Atmospheric Sounding Observation and Its Impact on Numerical Weather Prediction during Spring Season over the Continental United States

1
Meteomatics AG, Unterstrasse 12, 9000 St. Gallen, Switzerland
2
Space Science and Engineering Center, University of Wisconsin-Madison, Madison, WI 53706, USA
3
School of Environment, Nanjing Normal University, Nanjing 210098, China
*
Author to whom correspondence should be addressed.
Atmosphere 2023, 14(6), 967; https://doi.org/10.3390/atmos14060967
Submission received: 9 April 2023 / Revised: 27 May 2023 / Accepted: 29 May 2023 / Published: 1 June 2023
(This article belongs to the Special Issue Advances in Severe Weather Forecast)

Abstract

As a part of the World Meteorological Organization (WMO) Global Observing System, HIRAS-1 and HIRAS-2’s observations’ impact on improving the accuracy of numerical weather prediction (NWP) can be summarized into two questions: (1) Will HIRAS observation help the NWP system to improve its accuracy? (2) Which instrument has the greater impact on NWP? To answer the questions, four experiments are designed here: (I) the HIRAS-1 experiment, which assimilates the principal component (PC) scores derived from HIRAS-1 radiance observation from the FY-3D satellite; (II) the HIRAS-2 experiment, which assimilates HIRAS-2 (onboard the FY-3E satellite) radiance-observation-derived PC scores; (III) the J-01 experiment, which assimilates JPSS1 CrIS radiance-observation-derived PC scores; (IV) the control experiment. Each experiment generated a series of forecasts with 24 h lead-time from 16 March 2022 to 12 April 2022 using the Unified Forecast System Short-Range Weather application. Forecast evaluation using radiosonde and aircraft observation reveals: (a) for upper-level variables (i.e., temperature and specific humidity), assimilating HIRAS observation can improve the NWP’s performance by decreasing the standard deviation (Stdev) and increasing the anomaly correlation coefficient (ACC); (b) according to the multi-category Heidke skill score, HIRAS assimilation experiments, especially the HIRAS-2 experiment, have a higher agreement with hourly precipitation observations; (c) based on two tornado-outbreak case studies, which occurred on 30 March 2022 and 5 April 2022, HIRAS observation can increase the predicted intensity of 0–1 km storm relative helicity and decrease the height of the lifted condensation level at tornado outbreak locations; and (d) compared to CrIS, HIRAS-2 still has room for improvement.
Keywords: hyperspectral; infrared; data assimilation; numerical weather prediction hyperspectral; infrared; data assimilation; numerical weather prediction

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MDPI and ACS Style

Zhang, Q.; Shao, M. Assimilation of FY-3D and FY-3E Hyperspectral Infrared Atmospheric Sounding Observation and Its Impact on Numerical Weather Prediction during Spring Season over the Continental United States. Atmosphere 2023, 14, 967. https://doi.org/10.3390/atmos14060967

AMA Style

Zhang Q, Shao M. Assimilation of FY-3D and FY-3E Hyperspectral Infrared Atmospheric Sounding Observation and Its Impact on Numerical Weather Prediction during Spring Season over the Continental United States. Atmosphere. 2023; 14(6):967. https://doi.org/10.3390/atmos14060967

Chicago/Turabian Style

Zhang, Qi, and Min Shao. 2023. "Assimilation of FY-3D and FY-3E Hyperspectral Infrared Atmospheric Sounding Observation and Its Impact on Numerical Weather Prediction during Spring Season over the Continental United States" Atmosphere 14, no. 6: 967. https://doi.org/10.3390/atmos14060967

APA Style

Zhang, Q., & Shao, M. (2023). Assimilation of FY-3D and FY-3E Hyperspectral Infrared Atmospheric Sounding Observation and Its Impact on Numerical Weather Prediction during Spring Season over the Continental United States. Atmosphere, 14(6), 967. https://doi.org/10.3390/atmos14060967

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